Pedestrian Detection

Pedestrian detection is the task of detecting pedestrians from a camera.

Further state-of-the-art results (e.g. on the KITTI dataset) can be found at 3D Object Detection.

( Image credit: High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 201–225 of 438 papers

Title	Date	Tasks	Status
Pedestrian Detection by Exemplar-Guided Contrastive Learning	Nov 17, 2021	Contrastive LearningPedestrian Detection	—Unverified
Benchmarking person re-identification approaches and training datasets for practical real-world implementations	Sep 29, 2021	BenchmarkingPedestrian Detection	—Unverified
Traffic-Net: 3D Traffic Monitoring Using a Single Camera	Sep 19, 2021	3D Object DetectionCamera Auto-Calibration	—Unverified
Global-Local Dynamic Feature Alignment Network for Person Re-Identification	Sep 13, 2021	Pedestrian DetectionPerson Re-Identification	—Unverified
A Pedestrian Detection and Tracking Framework for Autonomous Cars: Efficient Fusion of Camera and LiDAR Data	Aug 27, 2021	Autonomous DrivingOptical Flow Estimation	—Unverified
Network Generalization Prediction for Safety Critical Tasks in Novel Operating Domains	Aug 17, 2021	Autonomous VehiclesPedestrian Detection	—Unverified
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study	Aug 3, 2021	Autonomous DrivingHuman Detection	—Unverified
Multi-Modal Pedestrian Detection with Large Misalignment Based on Modal-Wise Regression and Multi-Modal IoU	Jul 23, 2021	Pedestrian Detectionregression	—Unverified
You Better Look Twice: a new perspective for designing accurate detectors with reduced computations	Jul 21, 2021	Objectobject-detection	—Unverified
Efficient Learning of Pinball TWSVM using Privileged Information and its applications	Jul 14, 2021	BIG-bench Machine LearningHandwritten Digit Recognition	—Unverified
To the Point: Efficient 3D Object Detection in the Range Image with Graph Convolution Kernels	Jun 25, 2021	3D Object DetectionGraph Neural Network	—Unverified
Spatio-Contextual Deep Network Based Multimodal Pedestrian Detection For Autonomous Driving	May 26, 2021	Autonomous DrivingGraph Attention	—Unverified
Improved Instance Discrimination and Feature Compactness for End-to-End Person Search	May 21, 2021	Pedestrian DetectionPerson Re-Identification	CodeCode Available
Large-Scale Unsupervised Person Re-Identification with Contrastive Learning	May 17, 2021	Contrastive LearningDomain Adaptation	—Unverified
Verification of Size Invariance in DNN Activations using Concept Embeddings	May 14, 2021	Pedestrian Detection	—Unverified
Stable and Effective One-Step Method for Person Search	May 13, 2021	Multi-Task LearningPedestrian Detection	—Unverified
Pedestrian Detection in 3D Point Clouds using Deep Neural Networks	May 3, 2021	Autonomous DrivingPedestrian Detection	—Unverified
Segmentation-Based Bounding Box Generation for Omnidirectional Pedestrian Detection	Apr 28, 2021	object-detectionObject Detection	—Unverified
Computer vision in automated parking systems: Design, implementation and challenges	Apr 26, 2021	3D ReconstructionAutonomous Driving	—Unverified
Variational Pedestrian Detection	Apr 26, 2021	object-detectionObject Detection	—Unverified
Generalizable Multi-Camera 3D Pedestrian Detection	Apr 12, 2021	Generalizable Person Re-identificationPedestrian Detection	—Unverified
V2F-Net: Explicit Decomposition of Occluded Pedestrian Detection	Apr 7, 2021	Object DetectionPedestrian Detection	—Unverified
Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection	Mar 18, 2021	Autonomous DrivingPedestrian Detection	—Unverified
Multi-Scale Feature Pyramid Network: A Heavily Occluded Pedestrian Detection Network Based on ResNet	Mar 5, 2021	Object DetectionPedestrian Detection	—Unverified
Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person Search	Feb 22, 2021	Metric LearningMulti-Task Learning	CodeCode Available

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All datasets Caltech CityPersons LLVIP DVTOD TJU-Ped-traffic TJU-Ped-campus CVC14 Caltech Pedestrian Dataset MMPD-Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	UniHCP (FT)	Heavy MR^-2	27.2	—	Unverified
2	LDCF	Reasonable Miss Rate	24.8	—	Unverified
3	AlexNet	Reasonable Miss Rate	23.3	—	Unverified
4	TA-CNN	Reasonable Miss Rate	20.9	—	Unverified
5	Checkerboards+	Reasonable Miss Rate	17.1	—	Unverified
6	NNNF	Reasonable Miss Rate	16.2	—	Unverified
7	Part-level CNN + saliency and bounding box alignment	Reasonable Miss Rate	12.4	—	Unverified
8	CompACT-Deep	Reasonable Miss Rate	11.75	—	Unverified
9	MCF	Reasonable Miss Rate	10.4	—	Unverified
10	MS-CNN	Reasonable Miss Rate	9.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ACSP + EuroCity Persons	Heavy MR^-2	42.5	—	Unverified
2	TLL	Reasonable MR^-2	15.5	—	Unverified
3	FRCNN	Reasonable MR^-2	15.4	—	Unverified
4	FRCNN+Seg	Reasonable MR^-2	14.8	—	Unverified
5	TLL+MRF	Reasonable MR^-2	14.4	—	Unverified
6	RepLoss	Reasonable MR^-2	13.2	—	Unverified
7	OR-CNN	Reasonable MR^-2	12.8	—	Unverified
8	ALFNet	Reasonable MR^-2	12	—	Unverified
9	CSP (with offset) + ResNet-50	Reasonable MR^-2	11	—	Unverified
10	NOH-NMS	Reasonable MR^-2	10.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	INSANet	log average miss rate	4.43	—	Unverified
2	MMPedestron	AP	0.73	—	Unverified
3	CAFF-DINO	AP	0.69	—	Unverified
4	CFT	AP	0.64	—	Unverified
5	UniRGB-IR	AP	0.63	—	Unverified
6	RSDet	AP	0.61	—	Unverified
7	CMX	AP	0.6	—	Unverified
8	CSSA	AP	0.59	—	Unverified
9	GAFF	AP	0.56	—	Unverified
10	Halfway Fusion	AP	0.55	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	YOLOv6 (Thermal)	mAP	84.4	—	Unverified
2	YOLOv3 (Thermal)	mAP	82.7	—	Unverified
3	CFT	mAP	82.7	—	Unverified
4	CMX	mAP	81.6	—	Unverified
5	YOLOv7 (Thermal)	mAP	77.8	—	Unverified
6	YOLOv6 (Visible)	mAP	38.1	—	Unverified
7	YOLOv7 (Visible)	mAP	35.3	—	Unverified
8	YOLOv3 (Visible)	mAP	34.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FCOS	R (miss rate)	24.35	—	Unverified
2	RetinaNet	R (miss rate)	23.89	—	Unverified
3	FPN	R (miss rate)	22.3	—	Unverified
4	CrowdDet	R (miss rate)	20.82	—	Unverified
5	EGCL	R (miss rate)	19.73	—	Unverified
6	LSFM	R (miss rate)	18.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RetinaNet	R (miss rate)	34.73	—	Unverified
2	FCOS	R (miss rate)	31.89	—	Unverified
3	CrowdDet	R (miss rate)	25.73	—	Unverified
4	EGCL	R (miss rate)	24.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CFT	AP50	78.2	—	Unverified
2	CMX	AP50	68.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSFM	MR	0.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MMPedestron	box mAP	79	—	Unverified